How to Fix Costly Subpar Data at the Source

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As marketers increasingly rely on their own first-party data, the elephant in the room needs to be addressed: subpar data will yield subpar outcomes. In fact, according to Gartner, data of poor quality costs organizations an average of $12.9 million every year. 

The top culprit for costly, subpar data is subpar organizational practices. Organizing data can be quite the dramatic and daunting task, especially when there is a lack of consistency and unclear standards.

Here are the three best ways that marketers can start the journey of addressing data inconsistencies.

Get Ahead of the Problem

First and foremost: marketers should act swiftly in an effort to get ahead of the issue before it becomes a financial one. No matter the company size, a marketing ecosystem can be extremely complex and will likely require dozens of people working over several weeks to create basic marketing reports that ultimately help in client retention and business growth. It’s easy for errors to arise in this process. 

By diagnosing the issue and figuring out what its source is, marketers can breathe easier knowing that the root problem of subpar data is what’s being remedied as opposed to its unsatisfactory outcomes.

As opposed to conducting frequent data audits to ensure its quality, the implementation of a data management system can help keep all data complete, correct, and comparable across an organization’s many teams. Incomplete, incorrect, and uncomparable data will oftentimes yield results to match, leading to more resources being allocated for a solution. Therefore, parameters will need to be set in place first, as each organization will have different definitions of what is an “accurate” standard. Though this will require upfront work, standards help those who interact most heavily with various datasets to compare data from multiple sources on an even playing field.

Once in place, data standards can eliminate the need for marketers to adjust the outputs for inconsistencies after the fact, allowing for more robust conclusions to be drawn and fostering an environment where increased collaboration can be seen across teams. Implementing practices such as automating validation for pages, marketing tags, and a centrally managed data flow across a marketing ecosystem can result in up to 80% reduction in time spent on data quality processes.

More personalized experiences and increased digital engagement can be achieved because of richer data to make improved business decisions. Real-time insights on marketing initiative performance have contributed to improved decision making, new investments and team efficiency. 

Invest Internally

As a next step, marketers should consider investing in what is already close to home. A commitment from the top of the organization to prioritize its people, processes, and collaborative technologies will end up becoming a more strategic investment in the end. For example, more frequent and open communication between teams about the importance of quality and consistent data will help keep the priority top of mind. 

This internal cultural shift will allow for greater alignment for everyone involved, which will then pave the way for marketers to begin addressing how to solve the data inconsistency issue at the source.

Implement Standards Enterprise-wide

Once marketers have become acquainted with the ins and outs of data standards, a strategic next step would be to implement the standards practices across the enterprise as a whole. This wider adoption of standards will create a more cohesive and grounded collective, as opposed to various departments operating under different taxonomies.

Striking the right balance between structure, which is needed to ensure consistent data, and flexibility is key for an enterprise-wide adoption. Once the structure has been built, each team can customize to what they need. Meaning teams in different regions, functions, and product groups all can define a measurement strategy that makes sense for their goals, while still supporting the broader strategy for the whole organization.

The flexibility and willingness of all parties involved to adjust in order to seamlessly integrate these new procedures will ultimately lead to more efficient and effective ways of capturing the unique metadata that is needed in order to successfully run the business and accurately measure performance. 

With these few marching orders in mind, marketers can set themselves up for success in 2023 and onward. Pivoting in order to address problems before they become too much to correct should be every marketer’s primary focus these days. Though the thought of delaying the task at hand of implementing data standards may seem enticing, the payoff should most definitely be seen as an even greater offer.

EJ Freni is chief revenue officer at Claravine.

EJ is the Chief Revenue Officer for Claravine